Variation Of SO2 Concentration Research Articles

Air Quality Benefits From Implementing Best Available Techniques in Copper Mining and Smelting Complex Bor (Serbia)

Since 2016, the impact of the best available techniques (BAT) on air quality in Bor is significant. Its performance is presented by the air quality assessment with respect to the average annual sulfur dioxide (SO2) emitted concentrations and the total SO2 volume emitted per year from the smelter and sulfuric acid plant, relative to the quantity of processed concentrate in the period when production was conducted with the old technology, in 2013. Air quality in Bor was categorized as category III, i.e., the air was heavily polluted due to the exceeded tolerance of SO2 values. In the agglomeration Bor, during 2016/2017, air was of the category I, i.e., clean or slightly polluted air. The data illustrated that the temporal (yearly) variation of SO2 concentration was more influenced by human-related factors, especially by secondary industry share, as SO2 is mainly produced and discharged in the process of industrial production. The spatial variation of such concentration was more affected by meteorological indicators, especially by wind direction. In the period of the new technology, a significantly greater volume of concentrate was processed and a considerably larger quantity of cathode copper produced, and at the same time, total volume of emitted SO2 and measured heavy metals (lead-Pb, arsenic-As, cadmium-Cd, and nickel-Ni) was substantially reduced.

A Novel CMUT-Based Resonant Biochemical Sensor Using Electrospinning Technology

In this paper, a novel capacitive micromachined ultrasonic transducer (CMUT)-based resonant biochemical sensor is presented to detect SO2 with a sensitive polymer layer functionalized by electrospinning technology. The electrospinning technology is proposed as an innovative functionalization method to fabricate nano reticular polymer fibers with the diameters of 50–500 nm on the movable plates of the CMUTs. The surface topography of electrospun nanofibers and the impedance properties of functionalized CMUTs are characterized. The CMUT-based resonant biochemical sensor is packaged to detect SO2 in the experiments. Its resonant frequency shifts vary against the variation of SO2 concentration. The influences of the mixed gas flow rate are also analyzed. These show that the proposed sensor has good volume sensitivity and frequency stability.

Absorption of Sulfur Dioxide in Water with High Salinity

Understanding the absorption behaviour of sulphur dioxide in aqueous electrolyte solutions is of major interest for the design of flue gas desulphurization processes, as for example wet flue gas desulphurization of coal fired power plants or municipal solid waste incineration plants. In the present paper the influence of the water salinity on SO2 absorption is studied. The SO2 absortion was performed in equilibrium condition. The variation of marine solubility from 10 g/L to 40 g/L determines the variation of SO2 concentration in water from 2.6 mol/L to about 3.2 mol/L. In consequence, the variation of water salinity in these limits can detemine a quite big difference of water pollution.

Are the temporal variation and spatial variation of ambient SO2 concentrations determined by different factors?

Although previous studies have used panel data to identify factors influencing atmospheric contaminations, they generally trend to ignore the distinction between temporal variation factors and spatial variation factors of the pollution. In this study, a systematic investigation on the difference of the determinants driving the two types of variations of air pollution is addressed. We employed panel data models with both constant and varying coefficients to examine the impacts of socioeconomic factors (namely, population density, per capita GDP, and secondary industry share) and meteorological indicators (temperature, precipitation, and wind speed) on the spatial and temporal variation of ambient SO2 concentrations in China, using a sample of 30 major cities during the period 1995–2016. The results show that average SO2 concentrations for the 30 cities persistently declined over the 22 years studied, decreasing from 92 μg/m3 to 23 μg/m3, and that the most polluted cities shifted from being in the southwest to being in North China during this period. In addition, the gaseous pollutant concentrations and six factors were cointegrated. The results of the constant coefficient model (R2 = 0.734) indicate that secondary industry proportion presented a significant (p<1%) positive correlation with contamination; as such, a 1% increase in the secondary industry ratio was found to be able to cause a 0.81% increase in SO2 levels. The varying coefficient models (R2 = 0.922 and 0.839, respectively) illustrated that the temporal (yearly) variation of SO2 concentration was more influenced by human-related factors, especially by secondary industry share; as SO2 is mainly produced and discharged in the process of industrial production. While the spatial variation of such concentration was more affected by meteorological indicators, especially by wind speed. This may be caused by the large difference in climate conditions among the studied 30 cities.

An urban diffusion model for Delhi using computer techniques

A source oriented urban diffusion model for Delhi with area, elevated point and moving sources, based on the model developed by Hanna is utilised in obtaining spatial and temporal variations of SO2 concentrations, Average and maximum concentrations computed by the model fairly agreed with the monitored values.